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Abstract

The prediction of human motion intention is a key issue towards intelligent human robot interaction and robot navigation. In this work we present a comparative study of several prediction functions that are based on the minimum curvature variance from the current position to all the potential destination points, that means, the points that are relevant for people motion intention. The proposed predictor computes, at each interval of time, the trajectory from the present to the destination positions, and makes a prediction of the human motion at each interval of time using only the criterion of minimum curvature variation. The method has been validated in the Edinburgh Informatics Forum Pedestrian database.